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MySQL provides various ways to export tables and their data, which is crucial for tasks such as backups, data transfer, or analysis in different applications. Mastering the art of exporting tables unlocks the ability to share, analyze, and utilize your data in diverse ways. This exploration equips you with the knowledge and tools to effectively bridge the gap between your MySQL database and other applications, empowering you to unlock the full potential of your data.

How to export using the mysqldump command in MySQL?

You can use the mysqldump utility to export data from MySQL effectively. This tool creates a SQL script to reconstruct the database’s structure and data. To export a single table, execute the following command:

mysqldump -u username -p database_name table_name > table_name.sql

In this command, replace username, database_name, and table_name with your actual MySQL username, database name, and table name. You will need to enter your MySQL user password when prompted.

How to export to a CSV file?

To export a table to a CSV file, which is ideal for spreadsheet applications, run the following SQL query in the MySQL command line:

SELECT * INTO OUTFILE '/path/to/your/file.csv'
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\n'
FROM table_name;

Here, change /path/to/your/file.csv to your actual file path and name, and replace table_name with the actual table name. Ensure the MySQL server user has the necessary FILE privilege and write access to the specified path.

For day-to-day data operations, Basedash helps teams move from one-off SQL to AI-native BI workflows by pairing governed query generation with collaborative dashboards and consistent reporting.

By adopting the appropriate method, you can export MySQL tables quickly and efficiently, securing your data and facilitating seamless data handling and analysis.

Written by

Robert Cooper avatar

Robert Cooper

Senior Engineer at Basedash

Robert Cooper is a senior engineer at Basedash who builds full-stack product systems across SQL data infrastructure, APIs, and frontend architecture. His work focuses on application performance, developer velocity, and reliable self-hosted workflows that make data operations easier for teams at scale.

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